SIG-FIN-012-10

To clarify connections between social media data and nancial market data, we studied
the quantitative evaluations of relations between time series of word appearances on Japanese blogs
and those of stock prices. In particular, we proposed the method of comparison of some correlation
indices such as the Spearman's rank correlation coefficient, based on the man-made related stock
information. We found that the Spearman's rank correlation coefficients over time series of 562
keywords can hardly pick the correct combinations of related stocks out the pool of more than
3,000 stocks on the Tokyo Stock Exchange. However, we show that the composite correlation
indicators, which re
ect multiple features of the time series, can pick the correct stocks up to a
certain level of statically signicant.